Learning to Emulate Perception-Action Cycles in a Driving School Scenario (DRIVSCO)

Basic data for this project

Type of project: EU-project hosted outside University of Münster
Duration: 01/02/2006 - 31/07/2009

Description

Most technical systems, for example cars, must work reliably at key-turn. Therefore, such systems almost always employ conventional control strategies. Biological systems, on the other hand, learn. In the beginning they are functional only at a very basic level from which they improve their skills. No-one would, however, want to use a learning car, which could in the beginning barely steer. Thus, learning techniques have not really entered turn-key applications so far. The goal of DRIVSCO is to devise, test and implement a strategy of how to combine adaptive learning mechanisms with conventional control, starting with a fully operational human-machine interfaced control system and arriving at a strongly improved, largely autonomous system after learning, that will act in a proactive way using different predictive mechanisms.

Keywords: adaptive learning; human-machine interaction